Blockchain Papers

Makamba Biatrice Simbisai, Shylet Masunda

No abstract is available for this record.

Sonia Shahid

No abstract is available for this record.

C.A. Bindyashree, Chitra G., Syed Muzamil Basha, Hamed Taherdoost

In the present times, Transformation finance has become a prominent approach for a systematic financial channel to facilitate the step-by-step decarbonization of carbon-intensive sectors. Such mechanisms rely on the accuracy of carbon emissions data to measure environmental performance and to inform capital decisions. The current carbon accounting methods are limited by inadequate data-collection provisions, slow verification processes, and low auditability, which undermine the reliability of emission-reduction claims and constrain the effectiveness of carbon asset markets. In the present research work, a blockchain-based framework is proposed that will create reliable carbon data accounting and facilitate structured carbon asset circulation within ecosystems of transformation finance. The framework establishes a single carbon lifecycle for data, integrating real-time emission tracking, multi-step verification, a secure registry, and computer-generated assets. The datasets of industrial emissions used to test the operation of the proposed system under multi-sector conditions include energy systems and manufacturing activities, logistics networks, and urban service infrastructure. The objective of the proposed framework is to measure the reliability of carbon accounting by normalizing emission intensities, estimating verification confidence, and scoring trust with uncertainty. In addition, a circulation model is proposed to describe the liquidity of carbon assets, the efficiency of their utilization, and the stability of decentralized transactions. The outcome of the present research is to regulate the creation and transfer of tokenized carbon assets, which guarantees the consistency of environmental performance and financial representation. The review shows a quantifiable increase in the visibility of emission records, a decrease in verification delays, and greater visibility into asset circulation processes compared with traditional centralized systems. The suggested framework establishes a logical link between verifiable carbon-reduction results and decentralized financial mechanisms, enhancing the operational feasibility of transformation finance.

Zhiyuan Chen, Qiaoyun Gong, Jianhong Zhou

Enabled by blockchain progress, ICOs emerged as an alternative to traditional equity financing, with global investor reach, decentralized governance, and reduced transaction costs. However, the performance of ICOs under competitive product market conditions remains underexplored. This paper develops a game theoretic Cournot competition model to compare firms' financing and operational strategies under two benchmark scenarios, depending on whether product value is insensitive or sensitive to managerial effort. The analysis examines how cost structure, market volatility, product substitutability, and managerial risk attitude jointly affect financing choices and production decisions. To ensure research rigor, we further analyze a generalized model and conduct robustness checks by varying key parameters, confirming the stability of the equilibrium outcomes beyond the benchmark settings. The results show that optimal financing choices depend critically on market structure. Greater product substitutability intensifies competition and widens the utility gap between financing modes, strengthening the dominance of the more suitable strategy. Equity financing is more favorable for risk averse firms or those operating in low innovation, high substitutability industries such as manufacturing and utilities, due to its risk sharing and operational flexibility. In contrast, ICOs are better suited for innovation driven ventures such as DeFi and NFTs, which benefit from incentive alignment and reduced equity dilution. This study provides managerial insights into the strategic selection of financing mechanisms under competition and contributes to a deeper understanding of token financing in modern capital markets.

Jie He, Haiyan Cheng

Effective risk management has grown more and more crucial in the complex world of international trade finance, bolstered by security, trust, and openness. By creating an integrated system that blends Hyperledger Fabric blockchain technology, Supply Chain Finance (SCF) protocols, and Generative Adversarial Networks (GANs), this study seeks to improve the intelligence and dependability of financial risk assessment. Four interrelated steps make up the suggested approach: (1) preprocessing and encoding SCF datasets; (2) creating synthetic risk data with GANs to mimic uncommon or dishonest trade behaviors; (3) using Hyperledger Fabric to execute smart contracts and log transactions decentralized; and (4) using real-time SCF compliance modeling for dynamic risk assessment. While blockchain guarantees the transparency, immutability, and auditability of financial records, GAN integration improves the prediction model by adding value to the training corpus. Comparative studies show that the suggested system considerably lowers the likelihood of data tampering and improves risk prediction accuracy by 12% when compared to traditional machine learning models. The results demonstrate that integrating generative modeling with blockchain technology can significantly improve financial risk management, transparency, and adaptability in global trade settings.

Sara Gace, Julian Rode

The Vjosa River Basin, located in the heart of the Balkans, is one of Europe's last free-flowing wild rivers comprising a large number of pristine habitat types with a wealth of biodiversity. Widespread degradation of the forest ecosystem and unsustainable land use due to logging and livestock farming have led to an urgent need for effective conservation planning and sustainable management. This study applies the Ecosystem Service Opportunity (ESO) framework to provide a diagnosis of the social-ecological context and the current institutional and legal frameworks governing the Vjosa River in Permet area and its surroundings. Based on 15 semi-structured interviews with stakeholders from local government, NGOs, and a national government agency, we identify opportunities for policy and finance instruments to encourage ecosystem conservation and sustainable livelihoods. The results are compared to Integrated Management Plan (IMP) for the Vjosa Wild River National Park. Our results align with the IMP approach in several strategic areas (i.e., stronger law enforcement and patrolling, regulating illegal livestock grazing, improved staff management and collaboration between local agencies, incorporating traditional knowledge in conservation strategies), but further emphasizes the need for action beyond national park boundaries, decentralization with stronger municipal involvement, establishment of a collaborative platform, and the diversification of funding initiatives.

Balaram Tripathy

Enterprises are rapidly shifting from human-interpreted dashboards to Autonomous Analytical Entities (AAE) that execute decisions directly on production systems. This transition introduces a new failure mode—Agentic Divergence—where decentralized agents act on misaligned, drifted, or out-of-scope data products and metadata, leading to high-impact errors at scale. This paper proposes the Autonomous Analytical Coherence (AAC) framework, centered on an Analytical Control Plane (ACP) that inserts a mandatory, machine-enforced governance layer between AAEs and decentralized data products. The ACP mandates Agentic Data Contracts (ADC) as runtime dependencies and enforces Kullback–Leibler (KL) divergence-based drift checks within Trusted Execution Environments (TEE) to safeguard both analytical coherence and data sovereignty. Simulation-based experiments across finance and logistics workloads indicate that AAC reduces erroneous autonomous transactions by 77% compared with uncoordinated agent deployments, with only a 25 ms median increase in latency. These results demonstrate that treating governance as a runtime dependency is a practical path toward safe, high-stakes autonomous analytics in enterprise data meshes.

Radovan Vladisavljević, Aleksandra Zlatić-Tešić, Svetlana Marković

The aim of the work is to present a model of tax control automation using smart contracts, this is a relatively new application of blockchain technologies. The use of new technologies can greatly improve the operations of modern organizations that have digitized their operations. New technologies not only provide a high degree of automation but also provide a high degree of transparency. This leads to faster business with an increase in the level of trust of all participants in the business venture.

Sina Ahmadi Kaliji, Luca Camanzi

No abstract is available for this record.

Elvira Albert, Samir Genaim, Enrique Martin-Martin

Abstract Many compilation stages of smart contracts on the Ethereum blockchain have been transitioned to the intermediate language . Tasks such as smart contract optimization and bytecode generation are—or will soon be—performed directly at the level in the compilers for the higher-level languages such as Solidity. In this paper, we develop a formal semantics of programs in Rocq, suitable for verification, which allows formal reasoning at the level of code or generation tools processing programs. Our semantics is expressive enough to be the basis for formal verification tools, and simple enough to make the development of such tools feasible. In order to prove its adequacy for verification, we develop in Rocq a checker (and associated soundness proofs), based on our semantics, able to verify the results of the liveness analysis stage of the official Solidity compiler , which opens the door towards formally verified Ethereum’s smart contracts compilation. Experiments on more than 1,500 smart contracts show that we are able to automatically verify ’s liveness analysis results in negligible time.

Ritika Dhaneshwar

No abstract is available for this record.

Andrea Stazi

The incessant development and ubiquitous diffusion of information and communication technologies give rise to phenomena of considerable socio-economic and therefore legal significance. Among these, contractual relationships are strongly affected by technological evolution, which provides new tools for negotiating, concluding and executing contracts, with specific operating dynamics and unpublished legal issues. In this perspective, from a legal point of view, the contract-technology combination represents a topical issue for a comparative analysis, which provides the interpreter with an overall view of different local responses to common developments and problems deriving from the use of technology in contracts.

Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran

No abstract is available for this record.

Arseniy Vladimirovich Svetskiy

The article is devoted to the philosophical, legal and comparative legal analysis of the transformation of the autonomy of the will in the context of algorithmization of private law. The subject of the study is the transformation of the autonomy of the will as a system-forming principle of private law in the context of algorithmization of contractual relations. The focus is on the relationship between automaticity of fulfillment of obligations (smart contracts) and dispositivity, as well as the functional change in the role of the subject of civil law in the digital environment. In this paper, attention is paid to the problem of the relationship between automaticity of fulfillment of obligations and dispositivity as a system-forming principle of contract law. The author proceeds from the historiographical understanding of the autonomy of the will, which has developed in European and Russian civil law, and considers the smart contract as a technological form of realization of the previously expressed will of the parties. Additionally, the limits of judicial control and the preservation of traditional principles of good faith and proportionality in algorithmic mandatory structures are analyzed. The research methodology is based on a combination of philosophical-legal and comparative-legal approaches. The author applies a formal dogmatic method to analyze the category of autonomy of will and the legal nature of a smart contract in Russian civil law. The scientific novelty of the article lies in substantiating the thesis that the algorithmization of private law, contrary to the doctrinally widespread ideas about the "death of the subject" and the replacement of the autonomy of the will by program code, leads not to the denial of the classical model of the contract, but to the functional transformation of the role of the subject. Based on a comprehensive comparative legal analysis (Russia, the countries of continental Europe, the USA, China), the predominance of an integration regulatory model has been revealed, in which a smart contract adapts to existing legal structures without revising the conceptual core of the law of obligations. A comparative legal analysis of the regulation of smart contracts in Russia, the countries of continental Europe, the USA and China demonstrates the predominance of an integration model in which digital technologies adapt to existing legal structures without revising the conceptual core of the contract. The conclusion is drawn that the subject of private law in the era of algorithms does not lose its autonomy, but becomes the architect of its own digital normativity, while maintaining the status of a bearer of will and legal responsibility.

MartinaLužicová

This bachelor’s thesis deals with the topic „ Bitcoin – inception, development, future “, focusing on the operating principles of Bitcoin and the blockchain technology that underpins it. The theoretical part explains the key concepts related to cryptocurrencies and then characterizes Bitcoin, including its origin, the mining mechanism, and the significance of halving. The thesis also discusses altcoins, alternative cryptocurrencies that emerged after Bitcoin. The thesis includes an analysis of Bitcoin’s historical price development and identifies selected factors that have influenced its price cycles, volatility, and investor sentiment. Subsequently, it presents a fundamental analysis of Bitcoin, taking into account its specifics as an asset without traditional cash flow, and draws on selected market and on-chain metrics as well as qualitative project factors. A separate chapter is devoted to the regulatory environment in selected jurisdictions and its impact on the market.

Aitor Gómez-Goiri, David García-Estévez, José-Tomás San-José Lombera, Iván Gutiérrez-Agüero

No abstract is available for this record.

Jiazheng Lin, Yingying Wang

ABSTRACT The increasing complexity and interdependence of global supply chains necessitate innovative solutions to enhance collaboration while safeguarding data privacy. This paper presents a lightweight multi‐blockchain framework designed to address the challenges of privacy‐preserving collaboration in Internet of Things (IoT)‐driven supply chains. By integrating multiple blockchain networks, the proposed framework ensures data confidentiality, integrity, and traceability across various stakeholders. The system employs advanced cryptographic techniques, including zero‐knowledge proofs and differential privacy, to protect sensitive information during data exchange and processing. Additionally, the framework incorporates lightweight consensus mechanisms to accommodate the resource constraints of IoT devices. Experimental evaluations demonstrate the effectiveness of the proposed framework in improving data privacy and system scalability compared to existing solutions.

Hailang Cai, Yuwei Xu, Tianhua Li, Qiao Xiang · 6 authors

No abstract is available for this record.

Maria Smith

[Depreciated and replaced by V3] The application-specific clean rebuild has not yet been published; its authoritative theoretical boundary is now the governing V3 branch: After Turing: The Fold Machine - An Exact, Parameter-Free and Machine-Closed Derivation of Classical Computational Science from Smithian Fold Theory; From Fold to Consciousness: An Exact, Zero-Parameter and Machine-Closed Foundational Reconstruction of Consciousness and Cognitive Science from Smithian Fold Theory. The V3 source platform is https://github.com/MettaMazza/ernos-labs-sft-platform. The original DOI, concept DOI, version number and files are preserved for transparent historical provenance; this record must not be presented or cited as current V3 work. v4.0 — the word-scale gap closes within the fold. Rung 5e (pre-registered): the fold-factor mixing law — every context level that holds contributes, weighted 2^level, the engine's own forced halving constant — carries the pure counted engine, with no twin, no prose flood, zero training and zero parameters, past the gradient-trained transformer at word scale: cross-entropy 3.1907 vs the same-day twin's 3.4292 (replicated across two independent anchorings; stacked with the Rung 5d extraction: 3.1344). Both scales of the task gate now belong to the counted engine. Rung 5d's transfer-in verdict is SUPPORTED across three independent arena anchorings in one day. New in the architecture: tool graduation (acts held, values never — a question territory that a tool answered once runs the tool itself thereafter, fresh), recall as regeneration across every memory tier, and judge-independent graduation scoring. End-to-end verification: 36/36. v3.4: Rung 5d, the transfer-in — pre-registered verdict SUPPORTED: the trained twin's dyadically-loud fold content is extracted and installed INTO the counted engine as a counted prior with zero new parameters, closing 55.6/87.9/101.4% of the available gap at k=16/32/64 while the random-truncated null closes 10.1/24.5/56.5%; at half budget the loud shape beats the full twin's own. The word-scale rematch is recorded in full (twin retrained on today's text; decomposition included). Also: judge-independent graduation scoring (boot-discovered pool, cycle-parity alternation), multi-orbit binding (XI-4 in full), recall-is-regeneration (a held experience re-walks its own orbit, never reprinted), the public SOTA table beside the local giants with cited published figures, and one-command replication kits (GPT-2 weights auto-fetch; 13/13, 39/39 proven on a fresh clone). End-to-end verification: 36/36. Full paper v1.1 — supersedes the pre-paper (From One Axiom to Master-Level Chess — and the Law Inside Neural Networks). Built from scratch by one woman, working alone, in under twenty-four accumulated hours: where a score falls short it marks an implementation gap at measurement time, never a limit of the mathematics — the gains between releases are the finding. v1.4 adds the fold eye (vision as exact integer Walsh spectra, self-certified by integer Parseval per image, recognition of seen images with no image model in the loop) and the graduation score (blind head-to-head vs the teacher, tallied per question-territory; the teacher retires as wins cross the majority lock) -- and documents the 2026 convergence: DeepSeek Engram arrives at deterministically-addressed exact memory from the gradient side, and two independent results place the optimal curriculum at p = 1/2, the fold lock. v1.6: the full omnimodal engine (the voice via Kokoro, the fold ear -- sound as Parseval-certified integer Walsh spectra, video composed from frames + sound), speaker-transparent reasoning threads, and 32/32 end-to-end empirical verification of the entire architecture including persistence across process death. v1.7: removal-proof omnimodality, measured -- every supporting model is a teacher with an exit: a sound taught once by the synthesis teacher is re-spoken from the engine's own exact counted record in 0.00s with no model; a sound heard once is recognized natively with no transcriber; 34/34 end-to-end verification. v1.9: zero-model perceptual learning (the human observer -- a novel image learned and re-recognized at share 1.00 with no model in the loop); agentic self-knowledge (the observer reads the engine's own source, measured); the hourly progress instrument with a committed pre-boot birth line; one-tap y/n closure. v2.0 (flight-ready): the full modern-agent toolkit (live web search/fetch, paginated reading, in-file grep -- every call held as a training trace), the 43-domain everything-curriculum under the fold-only law, SOTA 1-1 benching on the public MMLU test split with the newborn baseline committed, generation closure (the Learning Law reaches generate() itself), and 36/36 end-to-end verification. v2.1: the ReAct law (reason-act-observe enforced in-turn; narrated intent without an act is detected and forced), reasoning trained on the observer's NATIVE thinking tokens (STaR-gated) with both minds' full thinking streamed to the user, and document intake (a sent file is reading -- inboxed, counted, persistent). v2.2: the identity stated correctly -- UnisonAI is an OMNI MODEL (language, sight, hearing, speech, and video on one held memory), not a language model; LLMs remain the contrast class only. v3.0: the full-altitude rewrite -- the complete omni model documented at the same depth as the spectral science: thirteen sections, the architecture organ by organ with every measurement, Rung 5c as its own section, the empirical record and its committed birth line, 36/36 end-to-end verification, and the 2026 convergence. This paper is a PROOF of The Smithian Fold Theory of Everything, not the main event: the theory (one axiom, zero free parameters, 1,844 machine-verified forced checks) is at DOI 10.5281/zenodo.21182469 and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything -- run the prover yourself. The engine: github.com/MettaMazza/UnisonAI. v3.3: the LLM-native presence suite -- the exact registered protocol applied to GPT-2's entire knowledge-storage class: 13/13 tensors, 39/39 checks, unanimous (margins 3.4-79.3x); the flagship claim now rests on the flagship objects, with diffusion/speech models recast as cross-domain breadth. Three connected results and the architecture they force. First, a pre-registered, self-certifying spectral instrument shows trained neural-network weights carry placement-law in the dyadic (Walsh) basis: 18/18 unanimous on validated released models; the law concentrated in transformer expansion projections and token embeddings across three unrelated architectures (up to 230x chance in GPT-2), attention at chance; strictly training-caused (He-initialised controls at 1.0x); surviving 4-bit deployment quantization. A recipe map from 124M to one trillion parameters shows the law tracks training recipe, not scale or architecture — strongest carrier DeepSeek-R1-671B at 43–47x — and loud-recipe weights transform under the fold's transformation group exactly as solved game-theoretic value fields do. Second, the "learned similarity space" is a counted object: word kinship as exact co-occurrence shares reproduces semantic family structure (quark → lepton, neutrino, proton) with zero parameters and zero gradients. Third, UnisonAI: a complete language architecture in which every LLM mechanism — memory, attention, similarity, learning, prediction, generation — is replaced by a machine-verified law of the Smithian Fold Theory, zero trained parameters end to end. On identical held-out text the fold-native engine outperformed its trained transformer twin (cross-entropy 1.289 vs 1.888) after reading the corpus once (26 seconds) against 48,000 gradient readings (21 minutes per seed). Deployed as a live, continuously-learning agent whose teaching loop also runs autonomously: a teacher model asks, judges, and closes the learning law itself, and the engine self-plays against its own held lessons. Negative results reported in full with their scopes. Companion to The Smithian Fold Theory of Everything (DOI: 10.5281/zenodo.21182469; 307 suites, 1,844 forced checks, 0 failures). Engine and records: github.com/MettaMazza/UnisonAI and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything.

Wenhao Wang, Lulu Zhou, Aviv Yaish, Fan Zhang · 6 authors

No abstract is available for this record.

Ryann Cartor, Nathan Daly, Giulia Gaggero, Jason T. LeGrow · 6 authors

No abstract is available for this record.

Yassine Lkhalidi, Hatim Kharraz Aroussi, Achraf Tifernine, Hamza Majid

No abstract is available for this record.

Emir Osmanspahić

No abstract is available for this record.

Assane Ilboudo, Didier Bassolé, Désiré GUEL

No abstract is available for this record.